Design and performance evaluation of a lightweight wireless early warning intrusion detection prototype

Distributed, Ambient, and Pervasive Interactions

Askoxylakis

Chatziadam

2014

Abstract. Wireless network technologies offer ubiquitous broadband access to millions of users at an affordable cost. However, the broadband nature of the wireless medium make these networks vulnerable to a number of attacks. Malicious interference at the physical layer, and extended packet collisions at the medium access layer can cause significant DoS attacks. In this work, we show how off-the-shelf hardware can be used to create devastating DoS attacks in a IEEE 802.11 network. Moreover, we present two algorithms for attack detection that are based on the cumulative sum algorithm.

Section: Attack Detectionmentioning

confidence: 99%

Denial-of-Service Attacks in Wireless Networks Using Off-the-Shelf Hardware

Distributed, Ambient, and Pervasive Interactions

Askoxylakis

Chatziadam

2014

“…Here, an attacker can violate several characteristics of the communication protocol and cause packet collisions, exhausting sensors' resources. The authors in [40] show how a single adversary can cause severe performance degradation by violating several rules of the link layer protocol (back-off mechanism). Another popular attack is the Sybil attack where an adversary maliciously uses the identities of a number of sensors.…”

Section: Common Attacks Against Wsns and Cwsnsmentioning

confidence: 99%

“…Contributions that study the detection of attacks at the link layer include [40]. Here, an anomaly-based algorithm is presented considering the ratio of the corrupted packets over the correctly decoded packets as the metric that reveals jamming when the attacker's energy is emitted on the same channel.…”

Section: Link Layer Attack Detectionmentioning

confidence: 99%

Securing Cognitive Wireless Sensor Networks: A Survey

International Journal of Distributed Sensor Networks

Angelakis

Τράγος

2014

Wireless sensor networks (WSNs) have gained a lot of attention recently due to the potential they provide for developing a plethora of cost-efficient applications. Although research on WSNs has been performed for more than a decade, only recently has the explosion of their potential applicability been identified. However, due to the fact that the wireless spectrum becomes congested in the unlicensed bands, there is a need for a next generation of WSNs, utilizing the advantages of cognitive radio (CR) technology for identifying and accessing the free spectrum bands. Thus, the next generation of wireless sensor networks is the cognitive wireless sensor networks (CWSNs). For the successful adoption of CWSNs, they have to be trustworthy and secure. Although the concept of CWSNs is quite new, a lot of work in the area of security and privacy has been done until now, and this work attempts to present an overview of the most important works for securing the CWSNs. Moreover, a discussion regarding open research issues is also given in the end of this work.

“…Cumulative-sum algorithms for intrusion detection A number of ID algorithms have been proposed in the literature. In our previous studies, we investigated several metrics based on the SINR (or SNR) [4], [22], [23]. We found that the max-min approach, which considers the maximumminus-the minimum value of the SINR in a short window, and its average value in a long window, achieves the best performance.…”

Section: Intrusion Detection Using Compressed Sensingmentioning

confidence: 99%

“…Using SINR and a cumulative-sum (Cusum) algorithm, which has the ability to detect abrupt changes, we can successfully detect the jamming attacks launched at the physical layer of a WN. This algorithm is part of the intrusion detection prototype described in [4].…”

Section: Introductionmentioning

confidence: 99%

Physical-layer intrusion detection for wireless networks using compressed sensing

2012 IEEE 8th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)

Nikitaki

Tsakalides

2012

Abstract-The broadcast nature of wireless networks has been widely exploited by adversaries in order to cause severe denial-of-service attacks. Several algorithms are proposed in the literature for the detection and mitigation of such attacks at the physical and medium access layers. In this work, we combine recent advances in compressed sensing theory, along with a cumulative-sum anomaly-based algorithm, for the detection of physical-layer attacks. The algorithm considers a metric based on the Signal-to-Interference-plus-Noise-Ratio (SINR). Compressed sensing makes feasible the use of far fewer SINR measurements for effective intrusion detection. The performance evaluation based on real experimental data shows that attacks are detected with high accuracy using a small number of measurements.